Supervised feature selection for polarimetric SAR classification

International Conference on Signal Processing Proceedings, ICSP

Volumn 2015-January, Issue October, 2014, Pages 1006-1010

  Bai, Yu ^a   Peng, Dongqing ^a   Yang, Xiangli ^a   Chen, Lijun ^a   Yang, Wen ^a  

^a WUHAN UNIVERSITY   (China)

Author keywords

Classification; Feature selection; PolSAR; Sparse support vector machine

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); COMPUTATIONAL EFFICIENCY; CROPS; POLARIMETERS; SIGNAL PROCESSING; SUPPORT VECTOR MACHINES; SYNTHETIC APERTURE RADAR;

CLASSIFICATION TASKS; COMPUTATION COMPLEXITY; DISCRIMINATIVE FEATURES; DISCRIMINATIVE POWER; FEATURE SELECTION ALGORITHM; ORIGINAL ALGORITHMS; POLARIMETRIC FEATURES; POLSAR;

FEATURE EXTRACTION;

EID: 84988299726     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICOSP.2014.7015156     Document Type: Conference Paper

References (9)

1. Evans, D. L., and Van Zyl, J. 1., "Polarimetric Imaging Radar: Analysis Tools and Applications,"Progress In Electromagnetics Research, PIER 03, 371-389,1990.
2. Cloude, S. R., and Pottier, E., "An entropy based classification scheme for land applications of polarimetric SAR," IEEE Trans. Geosci. Remote Sens., Vol. 35, No. 1,68-78, January, 1997.
3. Chen, L. 1., Yang, W., Liu, Y, Sun, H.,"Feature evaluation and selection for polarimetric SAR image classification,",Proceedings of the 20 I 0 IEEE I Oth International Conference on Signal Processing (ICSP),2202-2205, Betiing, China, Oct. 2010
4. Haddadi, G., Sahebi, M., Mansourian, A.,"Polarimetric SAR feature selection using a genetic algorithm," Canadian Journal of Remote Sensing, Vol. 37, No. 1, 27-36, 2011.
5. Vapnik, V. N., The Nature of Statistical Learning Theory, SpringerVerlag, 1995
6. Tan, M. K., Wang, L., Tsang, J. W., "Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets,"Proceedings of the 27th International Conference on Machine Learning, Haifa, Israel, June 2010.
7. Ainsworth, T. L., and Lee, J. S. "Polarimetric SAR image c1assificationlExploiting optimal variables derived from multiple-image datasets ", Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 188-191,2004.
8. Tu, S. T., Chen, J. Y., Yang, W., Sun, H., "Laplacian Eigenmaps-based Polarimetric Dimensionality Reduction for SAR Image Classification," IEEE Trans. Geosci. Remote Sens., Vol. 50, No. I, 170-179, 2012.
9. Nguyen, M. H., Torre, F. De la, "Optimal Feature Selection for Support Vector Machines," Pattern Recognition, Vol. 43, No. 3, 584-591,2010.